Mandatory Tour Frequency#
The individual mandatory tour frequency model predicts the number of work and school tours taken by each person with a mandatory DAP. The primary drivers of mandatory tour frequency are demographics, accessibility-based parameters such as drive time to work, and household automobile ownership. It also creates mandatory tours in the data pipeline.
The main interface to the mandatory tour purpose frequency model is the mandatory_tour_frequency function. This function is registered as an Inject step in the example Pipeline.
Structure#
Configuration File:
mandatory_tour_frequency.yaml
Core Table:
persons
Result Field:
mandatory_tour_frequency
This model generates only True or False outcomes, and is structured as a binary logit model.
Configuration#
- settings activitysim.abm.models.mandatory_tour_frequency.MandatoryTourFrequencySettings#
Bases:
LogitComponentSettings
Settings for the mandatory_tour_frequency component.
- Config:
extra: str = forbid
- Fields:
- Validators:
update_sharrow_skip
»all fields
- field COEFFICIENTS: Path | None = None#
Coefficients filename.
This is a CSV file giving named parameters for use in the utility expression. If it is not provided, then it is assumed that all model coefficients are given explicitly in the SPEC as numerical values instead of named parameters. This is perfectly acceptable for use with ActivitySim for typical simulation applications, but may be problematic if used with “estimation mode”.
- Validated by:
update_sharrow_skip
- field CONSTANTS: dict[str, Any] = {}#
Named constants usable in the utility expressions.
- Validated by:
update_sharrow_skip
- field LOGIT_TYPE: Literal['MNL', 'NL'] = 'MNL'#
Logit model mathematical form.
- “MNL”
Multinomial logit model.
- “NL”
Nested multinomial logit model.
- Validated by:
update_sharrow_skip
- field NESTS: LogitNestSpec | None = None#
Nesting structure for a nested logit model.
The nesting structure is specified heirarchically from the top, so the value of this field should be the “root” level nest of the nested logit tree, which should contain references to lower level nests and/or the actual alternatives.
For example, this YAML defines a simple nesting structure for four alternatives (DRIVE, WALK, WALK_TO_TRANSIT, DRIVE_TO_TRANSIT) with the two transit alternatives grouped together in a nest:
NESTS: name: root coefficient: coef_nest_root alternatives: - DRIVE - WALK - name: TRANSIT coefficient: coef_nest_transit alternatives: - WALK_TO_TRANSIT - DRIVE_TO_TRANSIT
- Validated by:
update_sharrow_skip
- field SPEC: Path [Required]#
Utility specification filename.
This is sometimes alternatively called the utility expressions calculator (UEC). It is a CSV file giving all the functions for the terms of a linear-in-parameters utility expression.
- Validated by:
update_sharrow_skip
- field annotate_persons: PreprocessorSettings | None = None#
- Validated by:
update_sharrow_skip
- field compute_settings: ComputeSettings = ComputeSettings(sharrow_skip=False, fastmath=True, use_bottleneck=None, use_numexpr=None, use_numba=None, drop_unused_columns=True, protect_columns=[])#
Sharrow settings for this component.
- Validated by:
update_sharrow_skip
- field preprocessor: PreprocessorSettings | None = None#
Setting for the preprocessor.
- Validated by:
update_sharrow_skip
- field source_file_paths: list[Path] = None#
A list of source files from which these settings were loaded.
This value should not be set by the user within the YAML settings files, instead it is populated as those files are loaded. It is primarily provided for debugging purposes, and does not actually affect the operation of any model.
- Validated by:
update_sharrow_skip
- classmethod nests_are_for_nl(nests, values)#
Checks that nests are provided if (and only if) LOGIT_TYPE is NL.
- validator update_sharrow_skip » all fields#
Examples#
Implementation#
- activitysim.abm.models.mandatory_tour_frequency.mandatory_tour_frequency(state: State, persons_merged: DataFrame, model_settings: MandatoryTourFrequencySettings | None = None, model_settings_file_name: str = 'mandatory_tour_frequency.yaml', trace_label: str = 'mandatory_tour_frequency') None #
This model predicts the frequency of making mandatory trips (see the alternatives above) - these trips include work and school in some combination.